There are infinite events linked to processes running in various organizations which is expected to run error free. However, depending on the criticality of the events at the time of occurrence of any issues/faults in the processes due to error/mismatch, the business impact or technical performance is enormous. If unnoticed early, resolution of the same will take lot of time, leave aside technical complications for fixing it. To add, if the problem lies many levels below the multilayer process model, the impact is severe to the organization and the resolution may take lot of time and money. Thus early detection of the problem in the cycle and correcting the data in real time is utmost important.
The inventors here have recognized several technical problems with such conventional systems, as explained below. There are several technical challenges in the existing systems for identifying one or many problem areas early in the process cycle and other challenge exist in taking least possible time to rectify one or more problems that have occurred during the course of running the process model. Also, many times there are complaint about certain events in the process cycle which severely impacts organization's functions and technical performance, but resolution of these events become very difficult as data might get refreshed or updated with new set of data and old occurrence cannot be replicated. If there are multiple process levels, identifying and rectifying them in real time is a big challenge. Even re-running option of the rectified events may impact the outcome of end result.
Since in the existing case, replication of the problem is not a feasible option, only possible solution is to debug the problem or using database query or investigating the source systems, which are crude and most of the times tedious time taking empirical solutions which are not sustainable for long.